Mathematical modeling of multicellular tumor spheroids quantifies inter-patient and intra-tumor heterogeneity

In the study of brain tumors, patient-derived three-dimensional sphere cultures provide an important tool for studying emerging treatments. The growth of such spheroids depends on the combined effects of proliferation and migration of cells, but it is challenging to make accurate distinctions between increase in cell number versus the radial movement of cells. To address this, we formulate a novel model in the form of a system of two partial differential equations (PDEs) incorporating both migration and growth terms, and show that it more accurately fits our data compared to simpler PDE models. We show that traveling-wave speeds are strongly associated with population heterogeneity. Having fitted the model to our dataset we show that a subset of the cell lines are best described by a "Go-or-Grow"-type model, which constitutes a special case of our model. Finally, we investigate whether our fitted model parameters are correlated with patient age and survival.

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Publication Details

Journal
npj Systems Biology and Applications
Published
2025-02-15
DOI
https://doi.org/10.1038/s41540-025-00492-3
Citations
4
Primary Topic
Mathematical Biology Tumor Growth
Type
article
Field-Weighted Citation Impact
5.47

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article

Mathematical modeling of multicellular tumor spheroids quantifies inter-patient and intra-tumor heterogeneity

John T. Nardini, Kyle Nguyen, Sven Nelander, Kevin Flores et al.
4 citations
npj Systems Biology and Applications
Mathematical Biology Tumor Growth
5.47
article

Mathematical modeling of multicellular tumor spheroids quantifies inter-patient and intra-tumor heterogeneity

John T. Nardini, Kyle Nguyen, Sven Nelander, Kevin Flores, Cecilia C. Krona, A. Malik
article en
4 citations

Abstract

In the study of brain tumors, patient-derived three-dimensional sphere cultures provide an important tool for studying emerging treatments. The growth of such spheroids depends on the combined effects of proliferation and migration of cells, but it is challenging to make accurate distinctions between increase in cell number versus the radial movement of cells. To address this, we formulate a novel model in the form of a system of two partial differential equations (PDEs) incorporating both migration and growth terms, and show that it more accurately fits our data compared to simpler PDE models. We show that traveling-wave speeds are strongly associated with population heterogeneity. Having fitted the model to our dataset we show that a subset of the cell lines are best described by a "Go-or-Grow"-type model, which constitutes a special case of our model. Finally, we investigate whether our fitted model parameters are correlated with patient age and survival.

npj Systems Biology and ApplicationsVol. 11(1)
Uppsala University (SE), North Carolina State University (US), The College of New Jersey (US), Chalmers University of Technology (SE)
National Science Foundation, Chalmers Tekniska Högskola
Openalex Percentile: Top 5%
Mathematical Biology Tumor Growth
5.47
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Mathematical modeling of multicellular tumor spheroids quantifies inter-patient and intra-tumor heterogeneity — John T. Nardini, Kyle Nguyen, et al. · npj Systems Biology and Applications (2025) | TGRS Research Map | TGRS